Compact graph neural network models for node classification

Recent research on graph convolutional networks tend to increase the complexity and non-linearity of graph convolution operators. Many of these operators result in models exploiting a huge number of learnable parameters, that have to be tuned during the training phase. This aspect makes the applicat... View More